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当前行为
部署启动qanything-container-local该image的时候报错
期望行为
running
运行环境
- OS:win 10
- NVIDIA Driver:546.33
- CUDA:12.3.107
- Docker Compose:Docker Compose version v2.23.3-desktop.2
- NVIDIA GPU Memory:16
QAnything日志
2024-01-10 13:28:33 =============================
2024-01-10 13:28:33 == Triton Inference Server ==
2024-01-10 13:28:33 =============================
2024-01-10 13:28:33
2024-01-10 13:28:33 NVIDIA Release 23.05 (build 61161506)
2024-01-10 13:28:33 Triton Server Version 2.34.0
2024-01-10 13:28:33
2024-01-10 13:28:33 Copyright (c) 2018-2023, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
2024-01-10 13:28:33
2024-01-10 13:28:33 Various files include modifications (c) NVIDIA CORPORATION & AFFILIATES. All rights reserved.
2024-01-10 13:28:33
2024-01-10 13:28:33 This container image and its contents are governed by the NVIDIA Deep Learning Container License.
2024-01-10 13:28:33 By pulling and using the container, you accept the terms and conditions of this license:
2024-01-10 13:28:33 https://developer.nvidia.com/ngc/nvidia-deep-learning-container-license
2024-01-10 13:28:34
2024-01-10 13:28:34 /opt/nvidia/nvidia_entrypoint.sh: /workspace/qanything_local/scripts/run_for_local.sh: /bin/bash^M: bad interpreter: No such file or directory
2024-01-10 13:28:34 /opt/nvidia/nvidia_entrypoint.sh: line 49: /workspace/qanything_local/scripts/run_for_local.sh: Success
复现方法 | Steps To Reproduce
在docker-compose -f docker-compose-windows.yaml up qanything_local使用该命令时报错
备注 | Anything else?
6条答案
按热度按时间axkjgtzd1#
我也是,但我是Linux系统。
sudo docker-compose -f docker-compose-linux.yaml up qanything_local
日志:
milvus-minio-local是最新的
milvus-etcd-local是最新的
mysql-container-local是最新的
milvus-standalone-local是最新的
启动qanything-container-local ...完成
附加到qanything-container-local
qanything-container-local |
qanything-container-local | =============================
qanything-container-local | == Triton推理服务器 ==
qanything-container-local | =============================
qanything-container-local |
qanything-container-local | NVIDIA Release 23.05(build 61161506)
qanything-container-local | Triton服务器版本2.34.0
qanything-container-local |
qanything-container-local | Copyright (c) 2018-2023,NVIDIA CORPORATION & AFFILIATES。所有权利保留。
qanything-container-local |
qanything-container-local | 各种文件包括修改(c)NVIDIA CORPORATION & AFFILIATES。所有权利保留。
qanything-container-local |
qanything-container-local | 此容器映像及其内容受NVIDIA深度学习容器许可的约束。
qanything-container-local | 通过拉取和使用此容器,您接受本许可条款和条件:
qanything-container-local | https://developer.nvidia.com/ngc/nvidia-deep-learning-container-license
qanything-container-local |
qanything-container-local | /opt/nvidia/nvidia_entrypoint.sh: /workspace/qanything_local/scripts/run_for_local.sh: /bin/bash^M:错误的解释器:没有这样的文件或目录
qanything-container-local | /opt/nvidia/nvidia_entrypoint.sh:第49行:/workspace/qanything_local/scripts/run_for_local.sh:成功
qanything-container-local以代码126退出
svdrlsy42#
请执行以下命令。
由于某种原因,启动脚本已被更改为DOS格式,需要手动修改为UNIX格式。
3b6akqbq3#
我也是,但我是Linux。
sudo docker-compose -f docker-compose-linux.yaml up qanything_local
日志:
milvus-minio-local是最新的milvus-etcd-local是最新的mysql-container-local是最新的milvus-standalone-local是最新的Starting qanything-container-local ... done Attaching to qanything-container-local qanything-container-local | qanything-container-local | ============================= qanything-container-local | == Triton Inference Server == qanything-container-local | ============================= qanything-container-local | qanything-container-local | NVIDIA Release 23.05 (build 61161506) qanything-container-local | Triton Server版本2.34.0 qanything-container-local | qanything-container-local | Copyright (c) 2018-2023,NVIDIA CORPORATION & AFFILIATES。所有权利保留。qanything-container-local | qanything-container-local | 各种文件包括修改(c)NVIDIA CORPORATION & AFFILIATES。所有权利保留。qanything-container-local | qanything-container-local | 此容器映像及其内容受NVIDIA深度学习容器许可的约束。qanything-container-local | 通过拉取和使用容器,您接受本许可条款和条件:qanything-container-local | https://developer.nvidia.com/ngc/nvidia-deep-learning-container-license qanything-container-local | qanything-container-local | /opt/nvidia/nvidia_entrypoint.sh: /workspace/qanything_local/scripts/run_for_local.sh: /bin/bash^M: bad interpreter: No such file or directory qanything-container-local | /opt/nvidia/nvidia_entrypoint.sh:第49行:/workspace/qanything_local/scripts/run_for_local.sh:成功qanything-container-local以代码126退出
请参考最新指南。
ruyhziif4#
是否已有关于该错误的issue或讨论? | Is there an existing issue / discussion for this?
该问题是否在FAQ中有解答? | Is there an existing answer for this in FAQ?
当前行为 | Current Behavior
部署启动qanything-container-local该image的时候报错
期望行为 | Expected Behavior
running
运行环境 | Environment
QAnything日志 | QAnything logs
2024-01-10 13:28:33 ============================= 2024-01-10 13:28:33 == Triton Inference Server == 2024-01-10 13:28:33 ============================= 2024-01-10 13:28:33 2024-01-10 13:28:33 NVIDIA Release 23.05 (build 61161506) 2024-01-10 13:28:33 Triton Server Version 2.34.0 2024-01-10 13:28:33 2024-01-10 13:28:33 Copyright (c) 2018-2023, NVIDIA CORPORATION & AFFILIATES. All rights reserved. 2024-01-10 13:28:33 2024-01-10 13:28:33 Various files include modifications (c) NVIDIA CORPORATION & AFFILIATES. All rights reserved. 2024-01-10 13:28:33 2024-01-10 13:28:33 This container image and its contents are governed by the NVIDIA Deep Learning Container License. 2024-01-10 13:28:33 By pulling and using the container, you accept the terms and conditions of this license: 2024-01-10 13:28:33 https://developer.nvidia.com/ngc/nvidia-deep-learning-container-license 2024-01-10 13:28:34 2024-01-10 13:28:34 /opt/nvidia/nvidia_entrypoint.sh: /workspace/qanything_local/scripts/run_for_local.sh: /bin/bash^M: bad interpreter: No such file or directory 2024-01-10 13:28:34 /opt/nvidia/nvidia_entrypoint.sh: line 49: /workspace/qanything_local/scripts/run_for_local.sh: Success
复现方法 | Steps To Reproduce
在docker-compose -f docker-compose-windows.yaml up qanything_local使用该命令时报错
备注 | Anything else?
Please refer to the latest instructions.
xmjla07d5#
好的,它可以运行,但仅限于本地使用。
如果从局域网上的其他设备访问,会出现错误
结束控制台:
b09cbbtk6#
好的,它可以运行,但仅限于本地。
如果从局域网的其他设备访问,会出现错误
结束控制台:
安装时选择云服务,如图所示,然后输入宿主机的IP地址即可: